Most wireless data network systems must adapt to limited communication resources between a central node (such as an access point, a gateway, or a base station) and the associated end-node devices (also denoted as end nodes or end-node-instances). Wireless data network systems frequently employ star topologies between end nodes and a central node. In such systems, due to the one-to-many communication nature between the central node and the end nodes, the limited communication resources of the central node must be scheduled carefully and utilized efficiently.
Due to the broadcast nature of the wireless medium, a central node can efficiently multicast common data to a certain number of end-node devices by utilizing the broadcast medium, in order to save communication resources in terms of bandwidth, time, and energy.
However, to ensure the correct delivery of data, a multicast message usually needs to specify the list of recipients. Herein, the term “recipients” refers to the subset of the end-node devices which the data is to be delivered thereto. As a result of the broadcast nature of the wireless medium, even an end-node device not included in the subset can also receive the multicast message. Therefore, each message receiver must check whether or not it is among the recipient list. The data is delivered only if the receiver is among the recipients.
Directly including the IDs of all the recipients into the multicast message may lead to an overly long message. US Patent Application Publication No. 2016/0218833 teaches a method to hash the recipients' IDs in order to compress them in a lossy way. However, the hashing-ID method may create false-positive match errors. For example, an end-node device not included in the recipient subset may find its ID matching the hashed IDs and thus, mistakenly consider itself as a recipient.
Since 2009, the Internet has been in a stage of its evolution in which the backbone (routers and servers) was connected to end nodes formed primarily by personal computers. At that time, Kevin Ashton (among others) looked ahead to the next stage in the Internet's evolution, which he described as the Internet of Things (IoT). In his article, “That ‘Internet of Things’ Thing,” RFID Journal, Jul. 22, 2009, he describes the circa-2009-Internet as almost wholly dependent upon human interaction. He asserts that nearly all of the data then available on the internet was generated by data-capture/data-creation chains of events, each of which included human interaction, e.g., typing, pressing a record button, taking a digital picture, or scanning a bar code. In the evolution of the Internet, such dependence upon human interaction as a link in each chain of data-capture and/or data-generation is a bottleneck. To deal with the bottleneck, Ashton suggested adapting internet-connected computers by providing them with data-capture and/or data-generation capability, thereby eliminating human interaction from a substantial portion of the data-capture/data-creation chains of events.
In the context of the IoT, a thing can be a natural or a man-made object which is assigned with a unique ID/address and which is configured with the ability to capture and/or create data and transfer that data over a network. Relative to the IoT, a thing can be e.g., a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low, field-operation devices that assist fire-fighters in search and rescue, personal biometric monitors woven into clothing that continuously and imperceptibly interact with thermostat systems and lighting systems to control HVAC and illumination conditions in a room, a refrigerator that is “aware” of its suitably tagged contents that can both plan a variety of menus from the food actually present therein and warn users of stale or spoiled food, and the like.
Within the small-device segment, the sub-segment that has the greatest growth-potential is the embedded low-power wireless devices. Networks of such devices are described as comprising the Wireless Embedded Internet (WET) which is a subset of IoT. More particularly, the WET end nodes include resource-limited embedded devices which are typically battery powered, and which are typically connected to form a network based on technologies such as low-power low-bandwidth wireless networks (LoWPANs) or LoRaWAN™ (LoRaWAN is a trademark of the LoRa Alliance of Beaverton, Oreg., U.S.A.).
By combining low-energy usage with long-range communication, both LoWPAN and LoRaWAN™ may be promising in providing connectivity suitable for large-scale, low-power, and low-cost IoT deployment with long battery lives such as up to ten years. The 2016 Cisco VNI 2015-2020 data traffic forecast estimates that the share of Low Power Wide Area networks in global machine-to-machine connections will grow from 4% in 2015 to 28% in 2020.
Those skilled in this art assumed that Moore's law would advance computing and communication capabilities so rapidly that soon any embedded device could implement IP protocols. However, this has not proven true for cheap low-power microcontrollers and low-power wireless radio technologies. The vast majority of simple embedded devices still make use of 8-bit and 16-bit microcontrollers with very limited memory because they are low-power, small, and cheap. Also, the physical trade-offs of wireless technologies have resulted in short-range low-power wireless radios which have limited data rates, frame sizes, and duty cycles, e.g., as in the IEEE 802.15.4 standard.
Consequently, most of the WET contains embedded devices having limited computation capability and communication resources. The communication between a central node and the end-node devices also suffers from such limitations.